Institute for Systems Engineering and Computers

The core component of most modern trackers is a discriminative classifier, tasked with distinguishing between the target and the surrounding environment. To cope with natural image changes, this classifier is typically trained with translated and scaled sample patches. Such sets of samples are riddled with redundancies-any overlapping pixels are constrained to be the same. Based on this simple observation, we propose an analytic model for datasets of thousands of translated patches. By showing that the resulting data matrix is circulant, we can diagonalize it with the discrete Fourier transform, reducing both storage and computation by several orders of magnitude. Interestingly, for linear regression our formulation is equivalent to a correlation filter, used by some of the fastest competitive trackers. For kernel regression, however, we derive a new kernelized correlation filter (KCF), that unlike other kernel algorithms has the exact same complexity as its linear counterpart. Building on it, we also propose a fast multi-channel extension of linear correlation filters, via a linear kernel, which we call dual correlation filter (DCF). Both KCF and DCF outperform top-ranking trackers such as Struck or TLD on a 50 videos benchmark, despite running at hundreds of frames-per-second, and being implemented in a few lines of code (Algorithm 1). To encourage further developments, our tracking framework was made open-source.

This paper describes and evaluates the feasibility of control strategies to be adopted for the operation of a microgrid when it becomes isolated. Normally, the microgrid operates in interconnected mode with the medium voltage network; however, scheduled or forced isolation can take place. In such conditions, the microgrid must have the ability to operate stably and autonomously. An evaluation of the need of storage devices and load shedding strategies is included in this paper.

This paper presents a conceptual framework to successfully integrate electric vehicles into electric power systems. The proposed framework covers two different domains: the grid technical operation and the electricity markets environment. All the players involved in both these processes, as well as their activities, are described in detail. Additionally, several simulations are presented in order to illustrate the potential impacts/benefits arising from the electric vehicles grid integration under the referred framework, comprising steady-state and dynamic behavior analysis.

Current methods struggle to reconstruct and visualize the genomic relationships of large numbers of bacterial genomes. GrapeTree facilitates the analyses of large numbers of allelic profiles by a static "GrapeTree Layout" algorithm that supports interactive visualizations of large trees within a web browser window. GrapeTree also implements a novel minimum spanning tree algorithm (MSTree V2) to reconstruct genetic relationships despite high levels of missing data. GrapeTree is a stand-alone package for investigating phylogenetic trees plus associated metadata and is also integrated into EnteroBase to facilitate cutting edge navigation of genomic relationships among bacterial pathogens.

Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs) is proposed. Images are classified in four classes, normal tissue, benign lesion, in situ carcinoma and invasive carcinoma, and in two classes, carcinoma and non-carcinoma. The architecture of the network is designed to retrieve information at different scales, including both nuclei and overall tissue organization. This design allows the extension of the proposed system to whole-slide histology images. The features extracted by the CNN are also used for training a Support Vector Machine classifier. Accuracies of 77.8% for four class and 83.3% for carcinoma/non-carcinoma are achieved. The sensitivity of our method for cancer cases is 95.6%.

Wearable Health Devices (WHDs) are increasingly helping people to better monitor their health status both at an activity/fitness level for self-health tracking and at a medical level providing more data to clinicians with a potential for earlier diagnostic and guidance of treatment. The technology revolution in the miniaturization of electronic devices is enabling to design more reliable and adaptable wearables, contributing for a world-wide change in the health monitoring approach. In this paper we review important aspects in the WHDs area, listing the state-of-the-art of wearable vital signs sensing technologies plus their system architectures and specifications. A focus on vital signs acquired by WHDs is made: first a discussion about the most important vital signs for health assessment using WHDs is presented and then for each vital sign a description is made concerning its origin and effect on heath, monitoring needs, acquisition methods and WHDs and recent scientific developments on the area (electrocardiogram, heart rate, blood pressure, respiration rate, blood oxygen saturation, blood glucose, skin perspiration, capnography, body temperature, motion evaluation, cardiac implantable devices and ambient parameters). A general WHDs system architecture is presented based on the state-of-the-art. After a global review of WHDs, we zoom in into cardiovascular WHDs, analysing commercial devices and their applicability versus quality, extending this subject to smart t-shirts for medical purposes. Furthermore we present a resumed evolution of these devices based on the prototypes developed along the years. Finally we discuss likely market trends and future challenges for the emerging WHDs area.

Informed driving is increasingly becoming a key feature for increasing the sustainability of taxi companies. The sensors that are installed in each vehicle are providing new opportunities for automatically discovering knowledge, which, in return, delivers information for real-time decision making. Intelligent transportation systems for taxi dispatching and for finding time-saving routes are already exploring these sensing data. This paper introduces a novel methodology for predicting the spatial distribution of taxi-passengers for a short-term time horizon using streaming data. First, the information was aggregated into a histogram time series. Then, three time-series forecasting techniques were combined to originate a prediction. Experimental tests were conducted using the online data that are transmitted by 441 vehicles of a fleet running in the city of Porto, Portugal. The results demonstrated that the proposed framework can provide effective insight into the spatiotemporal distribution of taxi-passenger demand for a 30-min horizon.

BACKGROUND: Multilocus Sequence Typing (MLST) is a frequently used typing method for the analysis of the clonal relationships among strains of several clinically relevant microbial species. MLST is based on the sequence of housekeeping genes that result in each strain having a distinct numerical allelic profile, which is abbreviated to a unique identifier: the sequence type (ST). The relatedness between two strains can then be inferred by the differences between allelic profiles. For a more comprehensive analysis of the possible patterns of evolutionary descent, a set of rules were proposed and implemented in the eBURST algorithm. These rules allow the division of a data set into several clusters of related strains, dubbed clonal complexes, by implementing a simple model of clonal expansion and diversification. Within each clonal complex, the rules identify which links between STs correspond to the most probable pattern of descent. However, the eBURST algorithm is not globally optimized, which can result in links, within the clonal complexes, that violate the rules proposed. RESULTS: Here, we present a globally optimized implementation of the eBURST algorithm - goeBURST. The search for a global optimal solution led to the formalization of the problem as a graphic matroid, for which greedy algorithms that provide an optimal solution exist. Several public data sets of MLST data were tested and differences between the two implementations were found and are discussed for five bacterial species: Enterococcus faecium, Streptococcus pneumoniae, Burkholderia pseudomallei, Campylobacter jejuni and Neisseria spp.. A novel feature implemented in goeBURST is the representation of the level of tiebreak rule reached before deciding if a link should be drawn, which can used to visually evaluate the reliability of the represented hypothetical pattern of descent. CONCLUSION: goeBURST is a globally optimized implementation of the eBURST algorithm, that identifies alternative patterns of descent for several bacterial species. Furthermore, the algorithm can be applied to any multilocus typing data based on the number of differences between numeric profiles. A software implementation is available at http://goeBURST.phyloviz.net.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper proposes a control scheme that allows doubly fed induction wind generators (DFIWG) to participate effectively in system frequency regulation. In this control approach, wind generators operate according to a deloaded optimum power extraction curve such that the active power provided by each wind turbine increases or decreases during system frequency changes. The control strategy defined at the wind generator to supply primary frequency regulation capability exploits a combination of control of the static converters and pitch control, adjusting the rotor speed and the active power according to the deloaded optimum power extraction curve. Results obtained in a small isolated system are presented to demonstrate the effectiveness of the approach. </para>

Wang Ling, Chris Dyer, Alan W Black, Isabel Trancoso, Ramón Fermandez, Silvio Amir, Luís Marujo, Tiago Luís. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. 2015.

Low-cost short read sequencing technology has revolutionized genomics, though it is only just becoming practical for the high-quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort, teams were asked to assemble a simulated Illumina HiSeq data set of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling, and copy number were made. We establish that within this benchmark: (1) It is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods. The simulated benchmark, including the correct answer, the assemblies, and the code that was used to evaluate the assemblies is now public and freely available from http://www.assemblathon.org/.

This paper proposes the utilization of water storage ability to improve wind park operational economic gains and to attenuate the active power output variations due to the intermittence of the wind-energy resource. An hourly-discretized optimization algorithm is proposed to identify the optimum daily operational strategy to be followed by the wind turbines and the hydro generation pumping equipments, provided that a wind-power forecasting is available. The stochastic characteristics of the wind power are exploited in the approach developed in order to identify an envelope of recommended operational conditions. Three operational conditions were analyzed and the obtained results are presented and discussed.

Experience economy is the last segment in the evolution of the market, and it is characterized by the fact that consumers do not acquire goods, products or services, but experiences that they integrate in their biography, and consequently in their identity. Customer Experience, possibly the latest revolution in business thinking along with the digital transformation, seeks the design and management of truly customer-centric experiences. This revolution is spreading across different sectors, among which the health sector should necessarily be considered. This talk covers the fundamental ideas within the concept of customer experience, as well as it provides information and suggestions about how to design and deliver an optimal patient experience.

This paper describes a genetic algorithm approach to the optimal multistage planning of distribution networks. The authors describe a mathematical and algorithmic model that they have developed and experimented with successfully. The paper also presents application examples, with real size systems. The advantages of adopting this new approach are discussed in the planning context, namely in conjunction with the adoption of multicriteria decision making methods.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

This paper provides a brief overview on the recent advances of small-scale unmanned aerial vehicles (UAVs) from the perspective of platforms, key elements, and scientific research. The survey starts with an introduction of the recent advances of small-scale UAV platforms, based on the information summarized from 132 models available worldwide. Next, the evolvement of the key elements, including onboard processing units, navigation sensors, mission-oriented sensors, communication modules, and ground control station, is presented and analyzed. Third, achievements of small-scale UAV research, particularly on platform design and construction, dynamics modeling, and flight control, are introduced. Finally, the future of small-scale UAVs' research, civil applications, and military applications are forecasted.

This paper proposes an optimized dispatch control strategy for active and reactive powers delivered by a doubly fed induction generator in a wind park. In this control approach, wind turbines are supposed to operate over a deloaded maximum power extraction curve and will respond to a supervisory wind farm control after a request from a system operator for adjusting the outputs of the wind park. The definition of the active and reactive powers operating points, for each wind turbine, is defined from an optimization algorithm that uses the primal-dual predictor corrector interior point method. The control strategy used at the wind generator level exploits a combination of pitch control and control of the static converters to adjust the rotor speed for the required operation points. A small wind park is used to illustrate the effectiveness of the developed approach.

Premium/IE3 efficiency class motors are now mandatory in North America. Super-Premium/IE4 and Ultra-Premium/IE5 efficiency classes are to be defined in the 2nd Edition of the IEC 60034-30 standard. For line-start fixed-speed applications, Super-Premium/IE4-class line-start permanentmagnet (PM) motors and squirrel-cage induction motors are recent entrances in the industrial motor market. For variable-speed applications, IE4-class synchronous reluctance motors are also a recent entrance in the market. For the low-power range, moving from the IE4 to the IE5 class may require moving away from radial-flux induction motor technology and into PM and reluctance technology, either using rare-earth or ferrite magnets. In this paper, efficiency analysis on the best available emerging electric motor technologies, such as axial-flux PM synchronous motors, is presented. The potential efficiency gain associated with several design options as well as some considerations on the theoretical maximum efficiency achievable taking into account those existing design options.

Intraplatoon information management strategies for dealing with safe and stable operation are proposed in this paper. New algorithms to mitigate communication delays are presented, and Matlab/Simulink-based simulation results are reported. We argue that using anticipatory information from both the platoon's leader and the followers significantly impacts platoon string stability. The obtained simulation results suggest that the effects of communication delays may be almost completely canceled out. The platoon presents a very stable behavior, even when subjected to strong acceleration patterns. When the communication channel is subjected to a strong load, proper algorithms may be selected, lowering network load and maintaining string stability. Upon emergency occurrences, the platoon's timely response may be ensured by dynamically increasing the weight of the platoons' leaders data over the behavior of their followers. The simulation results suggest that the algorithms are robust under several demanding scenarios. To assess if current intervehicle communication technology can cope with the proposed information-updating schemes, research into its operation was conducted through a network simulator.

Coating inkjet-printed traces of silver nanoparticle (AgNP) ink with a thin layer of eutectic gallium indium (EGaIn) increases the electrical conductivity by six-orders of magnitude and significantly improves tolerance to tensile strain. This enhancement is achieved through a room-temperature "sintering" process in which the liquid-phase EGaIn alloy binds the AgNP particles (≈100 nm diameter) to form a continuous conductive trace. Ultrathin and hydrographically transferrable electronics are produced by printing traces with a composition of AgNP-Ga-In on a 5 µm-thick temporary tattoo paper. The printed circuit is flexible enough to remain functional when deformed and can support strains above 80% with modest electromechanical coupling (gauge factor ≈1). These mechanically robust thin-film circuits are well suited for transfer to highly curved and nondevelopable 3D surfaces as well as skin and other soft deformable substrates. In contrast to other stretchable tattoo-like electronics, the low-cost processing steps introduced here eliminate the need for cleanroom fabrication and instead requires only a commercial desktop printer. Most significantly, it enables functionalities like "electronic tattoos" and 3D hydrographic transfer that have not been previously reported with EGaIn or EGaIn-based biphasic electronics.

The quasi-Z-source inverter (qZSI) with battery operation can balance the stochastic fluctuations of photovoltaic (PV) power injected to the grid/load, but its existing topology has a power limitation due to the wide range of discontinuous conduction mode during battery discharge. This paper proposes a new topology of the energy-stored qZSI to overcome this disadvantage. The operating characteristic of the proposed solution is analyzed in detail and compared to that of the existing topology. Two strategies are proposed with the related design principles to control the new energy-stored qZSI when applied to the PV power system. They can control the inverter output power, track the PV panel's maximum power point, and manage the battery power, simultaneously. The voltage boost and inversion, and energy storage are integrated in a single-stage inverter. An experimental prototype is built to test the proposed circuit and the two discussed control methods. The obtained results verify the theoretical analysis and prove the effectiveness of the proposed control of the inverter's input and output powers and battery power regardless of the charging or discharging situation. A real PV panel is used in the grid-tie test of the proposed energy-stored qZSI, which demonstrates three operational modes suitable for application in the PV power system.